Hugging Face's logo

VincentMuriuki
/
legal-summarizer

Summarization
Safetensors
English
t5
legal
Model card Files Community

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

Log in or Sign Up to review the conditions and access this model content.

Legal Document Summarizer

This model is fine-tuned from t5-base to summarize large legal documents like constitutions and finance bills. It simplifies complex legal language, making it more accessible to non-experts.

Training Data

The model was trained on a custom dataset of legal documents and their corresponding summaries.

Intended Use

  • Task: Legal document summarization.
  • Target audience: Legal professionals, researchers, and non-experts who need quick summaries of complex legal texts.
  • Input: A long legal document.
  • Output: A concise, simplified summary.

Usage 

from transformers import T5Tokenizer, T5ForConditionalGeneration

tokenizer = T5Tokenizer.from_pretrained("VincentMuriuki/legal-summarizer")
model = T5ForConditionalGeneration.from_pretrained("VincentMuriuki/legal-summarizer")

text = "Your long legal document here..."
inputs = tokenizer("summarize: " + text, return_tensors="pt", max_length=1024, truncation=True)
summary_ids = model.generate(inputs["input_ids"], max_length=150, min_length=50, length_penalty=2.0, num_beams=4, early_stopping=True)

summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
print(summary)
Downloads last month
42
Safetensors
Model size
223M params
Tensor type
F32
·
Inference Providers NEW
Summarization
This model is not currently available via any of the supported third-party Inference Providers, and HF Inference API was unable to determine this model's library.